Title :
Shape and Appearance Context Modeling
Author :
Wang, Xiaogang ; Doretto, Gianfranco ; Sebastian, Thomas ; Rittscher, Jens ; Tu, Peter
Author_Institution :
AI Lab, Cambridge
Abstract :
In this work we develop appearance models for computing the similarity between image regions containing deformable objects of a given class in realtime. We introduce the concept of shape and appearance context. The main idea is to model the spatial distribution of the appearance relative to each of the object parts. Estimating the model entails computing occurrence matrices. We introduce a generalization of the integral image and integral histogram frameworks, and prove that it can be used to dramatically speed up occurrence computation. We demonstrate the ability of this framework to recognize an individual walking across a network of cameras. Finally, we show that the proposed approach outperforms several other methods.
Keywords :
image processing; matrix algebra; appearance context modeling; image regions; integral histogram; integral image; occurrence matrices; shape context modeling; spatial distribution; Cameras; Computational complexity; Computer vision; Context modeling; Deformable models; Dictionaries; Histograms; Lighting; Robustness; Shape;
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2007.4409019